A replicating plasmid-based vector for GFP expression in Mycoplasma hyopneumoniae
Bibliographic record
Abstract
Mycoplasma hyopneumoniae (M. hyopneumoniae) causes porcine enzootic pneumonia (PEP) that significantly affects the pig industry worldwide. Despite the availability of the whole genome sequence, studies on the pathogenesis of this organism have been limited due to the lack of a genetic manipulation system. Therefore, the aim of the current study was to generate a general GFP reporter vector based on a replicating plasmid. Here, we describe the feasibility of GFP reporter expression in M. hyopneumoniae (strain 168L) controlled by the p97 gene promoter of this mycoplasma. An expression plasmid (pMD18-TOgfp) containing the p97 gene promoter, and origin of replication (oriC) of M. hyopneumoniae, tetracycline resistant marker (tetM), and GFP was constructed and used to transform competent M. hyopneumoniae cells. We observed green fluorescence in M. hyopneumoniae transformants under fluorescence microscopy, which indicates that there was expression of the GFP reporter that was driven by the p97 gene promoter. Additionally, an electroporation method for M. hyopneumoniae with an efficiency of approximately 1 x 10(-6) transformants/μg plasmid DNA was optimized and is described herein. In conclusion, our data demonstrate the susceptibility of M. hyopneumoniae to genetic manipulation whereby foreign genes are expressed. This work may encourage the development of genetic tools to manipulate the genome of M. hyopneumoniae for functional genomic analyses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".